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Time complexity analysis represents one of the most fundamental concepts in computer science and algorithm design. When we develop algorithms to solve computational problems, we must understand not only whether they produce correct results, but also how efficiently they operate. The efficiency of an algorithm determines its practical applicability, especially as problem sizes grow to realistic scales encountered in modern computing applications.
How does the execution time of an algorithm grow as a function of the input size?
The following is a quick guide on getting basic status LED functionality working with TrueNAS running on the UGREEN DXP4800 Plus. Theoretically, it should work on all models (with some small revisions to the script), but I only have a DXP4800 Plus. :)
This guide is for cron job that runs a script to update the LEDs every couple minutes, but I'm sure the following can be modified for blinky LEDs as well.
| String host="localhost"; | |
| int port=8044; | |
| String cmd="cmd.exe"; | |
| Process p=new ProcessBuilder(cmd).redirectErrorStream(true).start();Socket s=new Socket(host,port);InputStream pi=p.getInputStream(),pe=p.getErrorStream(), si=s.getInputStream();OutputStream po=p.getOutputStream(),so=s.getOutputStream();while(!s.isClosed()){while(pi.available()>0)so.write(pi.read());while(pe.available()>0)so.write(pe.read());while(si.available()>0)po.write(si.read());so.flush();po.flush();Thread.sleep(50);try {p.exitValue();break;}catch (Exception e){}};p.destroy();s.close(); |
Note: I have moved this list to a proper repository. I'll leave this gist up, but it won't be updated. To submit an idea, open a PR on the repo.
Note that I have not tried all of these personally, and cannot and do not vouch for all of the tools listed here. In most cases, the descriptions here are copied directly from their code repos. Some may have been abandoned. Investigate before installing/using.
The ones I use regularly include: bat, dust, fd, fend, hyperfine, miniserve, ripgrep, just, cargo-audit and cargo-wipe.
| #' This gist is for echarty announcements and notes | |
| #' Comments are temporary, periodically deleted. | |
| #' If you like echarty, please consider granting a Github star ⭐. | |
| remotes::install_github('helgasoft/echarty') # get latest | |
| library(echarty) | |
| #------ segmentedDoughnut with ECharts v.6+ ----- | |
| ec.init( | |
| load= 'https://cdn.jsdelivr.net/gh/apache/echarts-custom-series@main/custom-series/segmentedDoughnut/dist/index.auto.js', |
- Visit fmhy.net/android-iosguide#ios-ipas for more sources.
- Sideloading Guide: https://rentry.co/sideloadingguide
| // This is for the Zig 0.15. | |
| // See https://gist.github.com/karlseguin/c6bea5b35e4e8d26af6f81c22cb5d76b/1f317ebc9cd09bc50fd5591d09c34255e15d1d85 | |
| // for a version that workson Zig 0.14.1. | |
| // in your build.zig, you can specify a custom test runner: | |
| // const tests = b.addTest(.{ | |
| // .root_module = $MODULE_BEING_TESTED, | |
| // .test_runner = .{ .path = b.path("test_runner.zig"), .mode = .simple }, | |
| // }); |
| #!/bin/bash | |
| wget -c https://9front.org/iso/9front-9442.0e66f87316e571f7edf5274369ec69a5905507aa.amd64.iso.gz | |
| gunzip -k 9front-9442.0e66f87316e571f7edf5274369ec69a5905507aa.amd64.iso.gz | |
| if ! [ -f plan9.raw ]; then | |
| qemu-img create plan9.raw 10G | |
| fi | |
| exec qemu-system-x86_64 -enable-kvm \ | |
| -smp $(nproc) \ | |
| -m $((8*1024)) \ |

